The applications of such electro-optical systems more particularly relate to the field of defense where the development of autonomous devices such as drones, has required the development of 3D information extraction techniques on the environment of these devices.
Besides the new features associated with consumer technologies such as smart mobile phones or interactive gaming consoles, more and more often they use knowledge of the 3D environment around the user.
In both fields of application, the constraints specific to embedded systems require the designing of compact systems consuming little energy.
All mentioned devices have in common that they integrate at least one passive electro-optical system (a camera).
The object of the disclosure relates to the passive estimation of depth by exploiting data provided by the electro-optical system only, which is the least energy- and space-consuming method to add a 3D capacity to the device.
Single-channel distance estimation methods are known in the prior art.
U.S. Pat. No. 7,711,201 discloses a method and an electro-optical system for generating a depth map using a movable lens, an image sensor and a processing module coupled to the image sensor to determine the depth information. The lens, the image sensor and the processing module form an imaging device, such as a camera, used to capture an image of a scene for applications such as autofocusing, surveillance or autonomous vehicle navigation. A depth information calculation method includes a step of simulating a quantity of Gaussian blur using a convolution kernel, then an estimation of the difference of blur between the images.
The article by A. Levin, R. Fergus, F. Durand and W. T. Freeman, “Image and depth from a conventional camera with a coded aperture ACM Transactions on Graphics,” SIGGRAPH 2007 (available online at groups.csail.mitedu/graphics/CodedAperture/CodedAperture-LevinEtAl-SIGGRAPH07.pdf) describes a solution wherein distance is estimated from a single-channel electro-optical system implementing a coded diaphragm. It also describes a method for optimizing the encoding of such diaphragm.
French Patent FR2880958 discloses an electro-optical system for increasing the depth of field. One of the alternative solutions described in this patent relates to the implementation of a method and a system adapted for measuring the distance of objects in a scene from a single acquisition without requiring optical ranging equipment. The method then makes it possible to obtain an estimation of the distance of objects present in each region of the digital image.
The solution provided in this document of the prior art consists in using chromatic optics, which makes it possible to have a variable level of sharpness depending on the red, green and blue channels of the acquisition, and to break up the digital image into X by Y pixel zones. For each zone, the sharpness of at least two channels is then measured, and the measured values or the relative measured values are then reported onto sharpness vs. distance curves, i.e., curves defined, for example, by calibrating the capture device. A distance corresponding to an estimation of the depth of the part of the object shown in the capture device area in the reference mark of the device is then obtained.
This method then makes it possible to obtain an estimation of the distance of the objects present in each region of the digital image in order to build a real-time and low-cost optical ranging device with a sensor and standard optics, which gives an image and distance information correlated with the image.
The international application WO2009/082822 is also known, which describes a method for generating a depth map using a single camera, while selecting the best focus metric among the focus metric information from a set of captured images. The best metric makes it possible to determine the optimal lens position and to deduce the depth therefrom. This method of the prior art uses the depth map generated to execute an image processing operation, allowing, for example, adjusting the intensity of the flash, to re-focus the image on a depth plane of interest or to help generate a color image.
The international application WO2007/022329 describes another example of an image acquisition system generating a depth map from two images of a three-dimensional spatial scene based on the relative blur between the two images and the absolute blur produced by the system, calculating the depth map directly from the relative blur between the two images and calculating a distance from the associated blur radius value.
The U.S. patent application Ser. No. 2009/268985, filed Apr. 29, 2008, now U.S. Pat. 8,280,194, describes an imaging system that generates a picture depth map from a pair of reduced resolution images, computing a blur difference between the two reduced resolution images at different image locations and calculating the depth map based on the blur difference between the two reduced resolution images at different image locations.
European issued patent EP1734746 is also known, which describes a method for optimizing an electro-optical system based on a performance criterion for the image quality. This patent specifically describes a computer method for designing an electro-optical imaging system consisting of:                optical components;        an electro-optical detector and associated circuitry; and        digital processing means.        
This method of the prior art is based on a spatial model of the source. The method includes steps of jointly designing together, rather than sequentially, optical subsystems and digital image processing subsystems, based on a post-processing performance metric that depends on a comparison of a digital image calculated by the imaging system by the modelling with an ideal digital image of the source.
The article by A. Rajagopalan and S. Chaudhuri, “Performance analysis of maximum likelihood estimator for recovery of depth from defocused image and optimal selection of camera parameters,” International Journal of Computer Vision, Springer, 1998, 30, p. 175-190 is also known, which presents a method for optimizing the blur ratio of two images used to estimate the depth. This optimization is based on a depth estimation performance criterion, which is the Cramer-Rao bound calculated using a blur modelling by a Gaussian function and a parametric model of the source.